题目
Which of the following statements is correct regarding the usefulness of an autoregressive (AR) process and an autoregressive moving average (ARMA) process when modeling seasonal data? I. They both include lagged terms and, therefore, can better capture a relationship in motion. II. They both specialize in capturing only the random movements in time series data.
选项
A.I only.
B.II only.
C.Both I and II.
D.Neither I nor II.
答案
A
解析
Both autoregressive (AR) models and autoregressive moving average (ARMA) models are good at forecasting with seasonal patterns because they both involve lagged observable variables, which are best for capturing a relationship in motion. It is the moving average representation that is best at capturing only random movements.自回归（AR）模型和自回归移动平均（ARMA）模型都擅长使用季节性模式进行预测，因为它们都包含滞后的可观察变量，最适合捕获运动关系。 移动平均表示最适合仅捕获随机运动。